Most of the early wind erosion research undertaken in Australia, concentrated on how wind erosion affects cultivated farm land. However, in the 1990's the focus of wind erosion research in Australia started to shift to include rangeland environments. Initially these rangeland experiments used experimental configurations that were developed for cultivated fields. This meant that in most cases a sampler was set up in the middle of a field and it was assumed that the data collected was representative of the field as a whole. It was also assumed that temporal changes in dust fluxes/concentration reflect overall changes in the land type erodibility and wind erosivity. However, recent experiments and field observations within the rangelands, of the Channel Country suggest that this assumption is not valid. These experiments and observations suggest that there are substantial spatial and temporal variations in erodibility within individual land types. Such variations complicate the interpretation of temporal and spatial erosion trends. In particular, this variability implies that it is difficult to compare sampler data between different wind erosion events. To begin quantifying and comparing sampler data between events within the rangeland environments, the Dust Source Interaction Simulation Model (DSism) was developed to simulate the effect that physical processes and spatial variations in erodibility have upon observed dust concentration pro- files. The modelling/simulation approach used is closely linked to experimental data via the extensive use of sensitivity testing. Another key feature of the DSism approach, is its flexibility in allowing different dust source areas to have particle emission characteristics. This combined sensitivity testing and simulation approach has provided new insights into the wind erosion processes. By using DSism, it has been possible to identify several key features of the wind erosion process within rangeland environments. The first observation is that spatial and temporal changes in erodibility produce distinct changes in both the vertical and crosswind dust concentration profiles. Further investigations, indicate that the dispersion processes in operation vary from event to event. In particular, the results presented here indicate that surface heating plays an important role in some wind erosion events. These results also suggest that even small variations in the vertical dust concentration profile can reflect temporal and spatial changes in processes and erodibility. Finally the simulation results show that the particle size distribution of a vertical dust concentration profile depends on (a) the processes in operation during a given event and (b) the spatial variation in the particle size emission characteristics of the various source areas. These findings have several important implications. In particular, they indicate that both the crosswind and vertical dust concentration profiles can be viewed as amalgamation of several distinct plumes from different dust source areas and that dust concentration profiles contain significant information about both the spatial distribution of sources and the processes in operation during any given event. Most field studies have used regression models to describe the variation in dust concentration with height. A problem with this approach is that it assumes that the variation in dust concentration with height, always has a given functional form (or shape) and that dust concentration always decreases with height. Field observations, indicate that this assumption is only valid for some events within rangeland environments and that dust concentration does not always decrease with height in these environments. In most cases, such variations from the regression fit have been assumed to be the result of experimental 'noise' (error) or spatial variations in erodibility. This thesis presents, modelling and field evidence, which suggests that such variations, are the result of a combination of spatial variations in erodibility and changes in thermal conditions.

Over the past century, dust emissions have increased in frequency and intensity due to anthropogenic influences and extended droughts. Dust transports microbes, nutrients, heavy metals and other materials that may then change the biogeochemistry of the receiving environments. The purpose of this study was to find whether unique bacterial communities may provide distinct fingerprints of dust sources in the Western USA. We collaborated with the National Wind Erosion Research Network (NWERN) to identify bacterial core communities (core) of dust from ten NWERN sites, and compared communities to location, soil, and regional characteristics. In order of importance, precipitation levels (F = 43, P = 0.0001, Df = 2, r2 = 0.25), location (F = 16, P = 0.0001, Df = 5, r2 = 0.23), soil texture (F = 14, P = 0.0001, Df = 3, r2 =0.12), seasonality (F = 11, P = 0.0001, Df = 2, r2 = 0.064), and elevation (F = 5.7, P = 0.0002, r2 = 0.033) determined bacterial community composition. Bacterial core communities were defined as taxa present in at least 50% of samples at each site and offered predictable patterns of dust communities in terms of abundant (> 1% relative abundance) and rare (< 1% relative abundance) signatures. We found distinct bacterial core communities that reflected dust source systems, for example, sites contaminated with heavy metals contained Romboutsia, Turicibacter, Clostridium sensu stricto 1, Geodermatophilus, and Microvirga. Sites with association to plants and biocrusts contained Methylobacterium-Methylorubrum, Bradyrhizobium, Paenibacillus thermoaerophilus, Cohnella, and bacterial families Solirubrobacteraceae, Sphingobacteraceae, and Myxococcaceae. The presence of Sphingomonas, Stenotrophomonas, Rhodococcus, and Phenylobacterium were found in hydrocarbon contaminated soils. High stress (UV radiation and desiccation) sites contained Deinococcus, Blastococcus, and Modestobacter. We found that seasonal changes affected microbial community composition in five NWERN sites (CPER, HAFB, Jornada, Red Hills, and Twin Valley) (p < 0.05), while no seasonal effects on bacterial distribution were observed at Moab. Our results identify that the use of core microbiomes may offer a fingerprinting method to identify dust source regions.